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CONCLUSION: The developed viewer concept and its implementation facilitate a deeper insight and a better understanding of the development process of predictive models in the telehealth context.
PMID: 31118343 [PubMed - in process]

CONCLUSION: Referring to HL7 templates, our criteria can be applied to documents of national EHR systems such as ELGA and hereby reach a broad patient cohort. Implementing our approach within ART-DECOR alleviates its reuse and enhancement by other researchers.
PMID: 31118342 [PubMed - in process]

CONCLUSION: Initial results illustrate how a shift from paper-based documentation to an integrated eHealth service can improve communication and documentation in an independent therapy network.
PMID: 31118341 [PubMed - in process]

CONCLUSION: For the given scenario, our algorithm matched 74.5% of the patients. However, we had no gold standard for validating our results. Most of the free text annotations contained the expected values.
PMID: 31118340 [PubMed - in process]

This study aimed at determining the performance of health information management departments (HIMD) to identify the policies of these hospitals, their similarities, and differences in their procedures in this respect. Managers of the departments and information disclosure and medical record staff in 22 teaching hospitals were invited to complete a questionnaire regarding their practices in four axes including confidentiality principles, principles of disclosure consent, disclosure information to external and internal users. We found that there are no specific national framework and guidelines for the disclosure of health i...

Authors: Zechmeister M, Endel F
Abstract
In Austria, there is no single source of truth holding information about all physicians and their medical practice. Therefore, different sources have to be combined to accumulate detailed information about doctors, identify data errors and increase overall data quality. The aim of this project is to link two datasets from vastly different origins utilizing reproduceable and mostly automatic procedures in contrast to manually acquired links in the past. As there is no global identifier, names and addresses of the doctors were used instead. Because of different spellings and t...

In this study we explore machine learning approaches to infection severity recognition on driveline exit site images. We apply a U-net convolutional neural network (CNN) for driveline tube segmentation, resulting in a Dice score coefficient of 0.95. A classification CNN is trained to predict the membership of one out of three infection classes in photographs. The resulting accuracy of 67% in total is close to the measured expert level performance, which indicates that also for human experts there may not be enough information present in the photographs for accurate assessment. We suggest the inclusion of thermographic imag...

Authors: Veeranki SPK, Kramer D, Hayn D, Jauk S, Eggerth A, Quehenberger F, Leodolter W, Schreier G
Abstract
Adoption of electronic medical records in hospitals generates a large amount of data. Health care professionals can easily lose their sight on the important insights of the patients' clinical and medical history. Although machine learning algorithms have already proved their significance in healthcare research, remains a challenge translation and dissemination of fully automated prediction algorithms from research to decision support at the point of care. In this paper, we address the effect of changes in th...

Authors: Kriegel J, Grabner V, Tuttle-Weidinger L, Ehrenmüller I
Abstract
In-patient care of the elderly is currently being put to the test in all developed industrial nations. The aim is to make the resident-centered and nursing-related care more professional. In addition to the organizational and interdisciplinary orientation, the use of socially assistive robot technologies and artificial intelligence is increasingly coming to the fore. By means of literature research, expert interviews and an online survey of Upper Austrian nursing home directors, current and future challenges and challenges for the use of...

CONCLUSION: This computer-based ATM provided an effective, easy to use and cost-effective way of enabling blind and partially sighted people learn a cognitive map and enhance their wellbeing.
PMID: 31118334 [PubMed - in process]